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Condition on full signal

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This commit is contained in:
James Betker 2021-10-30 19:58:34 -06:00
parent e9dc37f19c
commit 83cccef9d8
1 changed files with 3 additions and 2 deletions
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codes/models/gpt_voice/unet_diffusion_vocoder_with_ref.py
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@ -121,7 +121,8 @@ class DiffusionVocoderWithRef(nn.Module):
self.conditioning_enabled = conditioning_inputs_provided self.conditioning_enabled = conditioning_inputs_provided
if conditioning_inputs_provided: if conditioning_inputs_provided:
self.contextual_embedder = AudioMiniEncoder(conditioning_input_dim, time_embed_dim) self.contextual_embedder = AudioMiniEncoder(in_channels, time_embed_dim, base_channels=32, depth=6, resnet_blocks=1,
attn_blocks=2, num_attn_heads=2, dropout=dropout, downsample_factor=4, kernel_size=5)
self.input_blocks = nn.ModuleList( self.input_blocks = nn.ModuleList(
[ [
@ -329,7 +330,7 @@ if __name__ == '__main__':
clip = torch.randn(2, 1, 40960) clip = torch.randn(2, 1, 40960)
#spec = torch.randint(8192, (2, 40,)) #spec = torch.randint(8192, (2, 40,))
spec = torch.randn(2,512,160) spec = torch.randn(2,512,160)
cond = torch.randn(2, 80, 173) cond = torch.randn(2, 1, 40960)
ts = torch.LongTensor([555, 556]) ts = torch.LongTensor([555, 556])
model = DiffusionVocoderWithRef(32, conditioning_inputs_provided=True, time_embed_dim_multiplier=8) model = DiffusionVocoderWithRef(32, conditioning_inputs_provided=True, time_embed_dim_multiplier=8)
print(model(clip, ts, spec, cond).shape) print(model(clip, ts, spec, cond).shape)